Google and IBM have joined up to teach university students about parallel computing.
Parallel computing is a method for computers to more quickly carry out large-scale tasks by simultaneously handling several different instructions through multiple processors. Google and IBM announced yesterday that they have developed a joint initiative to help computer science students gain more knowledge of highly parallel-computing practices.
Researchers at the University of Maryland, for instance, developed a parallel processing desktop computer this summer that they say runs 100 times faster than today's PCs.
Google and IBM noted that several common internet applications, including search engines, social-networking sites and mobile commerce, often need to have their computational tasks broken into hundreds of smaller parts that run simultaneously across different servers. They also said that parallel programming can be used for scientific purposes, such as gene sequencing and climate modelling.
To get their project up and running, Google and IBM have dedicated a cluster of several hundred processors that can be accessed by students over the internet to test parallel computing projects. Google and IBM said that the servers will run using open source software that will allow students to develop programs for clusters that run Hadoop, an open source application designed specifically for writing and running large applications.
Google and IBM said that the US University of Washington is the first university to join the initiative and that other US universities – Carnegie Mellon University, MIT, Stanford, UC Berkeley and the University of Maryland – will also pilot the program.
"Carnegie Mellon applauds Google and IBM for helping to provide resources that will help better prepare our students for the challenges presented by parallel computing," said Randal Bryant, the dean of Carnegie Mellon's School of Computer Science. "We are quite pleased to be among the first universities participating in this program."
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